Video data is typically composed of a series of still images which are shown rapidly in succession as a video sequence to give the idea of a moving image. Video applications are continuously moving towards higher and higher resolution. A large quantity of video material is distributed in digital form over broadcast channels, digital networks and packaged media, with a continuous evolution towards higher quality and resolution (e.g. higher number of pixels per frame, higher frame rate, higher bit-depth or extended color gamut). This technological evolution puts higher pressure on the distribution networks that are already facing difficulties in bringing HDTV resolution and high data rates economically to the end user.
Video coding is a way of transforming a series of video images into a compact bitstream so that the capacities required for transmitting and storing the video images can be reduced. Video coding techniques typically use spatial and temporal redundancies of images in order to generate data bit streams of reduced size compared with the original video sequences. Spatial prediction techniques (also referred to as Intra coding) exploit the mutual correlation between neighbouring image pixels, while temporal prediction techniques (also referred to as INTER coding) exploit the correlation between images of sequential images. Such compression techniques render the transmission and/or storage of the video sequences more effective since they reduce the capacity required of a transfer network, or storage device, to transmit or store the bit-stream code.
An original video sequence to be encoded or decoded generally comprises a succession of digital images which may be represented by one or more matrices, the coefficients of which represent pixels. An encoding device is used to code the video images, with an associated decoding device being available to reconstruct the bit stream for display and viewing.
Common standardized approaches have been adopted for the format and method of the coding process. One of the more recent standards is Scalable Video Coding (SVC) in which a video image is split into smaller sections (often referred to as macroblocks or blocks) and treated as being comprised of hierarchical layers. The hierarchical layers include a base layer, corresponding to lower quality images (or frames) of the original video sequence, and one or more enhancement layers (also known as refinement layers) providing better quality, images in terms of spatial and/or temporal enhancement compared to base layer images. SVC is a scalable extension of the H.264/AVC video compression standard. In SVC, compression efficiency can be obtained by exploiting the redundancy between the base layer and the enhancement layers.
A further video standard being standardized is HEVC, in which the macroblocks are replaced by so-called Coding Units and are partitioned and adjusted according to the characteristics of the original image segment under consideration. This allows more detailed coding of areas of the video image which contain relatively more information and less coding effort for those areas with fewer features.
The video images may be processed by coding each smaller image portion individually, in a manner resembling the digital coding of still images or pictures. Different coding models provide prediction of an image portion in one frame, from a neighboring image portion of that frame, by association with a similar portion in a neighboring frame, or from a lower layer to an upper layer (referred to as “inter-layer prediction”). This allows use of already available coded information, thereby reducing the amount of coding bit-rate needed overall.
Differences between the source area and the area used for prediction are captured in a set of residual values which themselves are encoded in association with a code for the source area. Effective coding selects the best model to provide the desired image quality at decoding, while taking account of the bitstream size required by each model to represent an image in the bitstream. A trade-off between the decoded image quality and reduction in required number of bits or bit rate, also known as compression of the data, is typically considered.
In general, the more data that can be compressed at a given visual quality, the better the performance in terms of compression efficiency.